1. mapview basics

mapview is intended to provide a quick and easy way to visualize/plot spatial data in an interactive manner. As such, a one-liner is enough to produce an interactive map view of the data. Methods are defined for all objects from packages sf, sp, raster and satellite.

Vector data

mapview includes 3 vector type data sets:

  • breweries - a selection of (micro-) breweries in Franconia, Bavaria.
  • trails - slected hiking trails in Franconia.
  • franconia - administrative regions of Franconia at the district level.

For vector data a call to mapview without any further arguments will produce a default map view including:

  • a layer control to switch between 5 different background maps
  • a scale bar
  • information on mouse cursor position and zoom level of the current view
  • a zoom-to-layer button to easily navigate to the displayed layer
  • popups listing all attribute entries of the respective features (when clicked)
  • labels of the feature IDs (when hovered over)
  • zoom control buttons provided by the underlying leaflet map
  • attribution information of the active map layer in the bottom right corener of the map

Here’s an example for each vector type:

Point data

library(mapview)
mapview(breweries)

Line data

mapview(trails)

Polygon data

mapview(franconia)

Controlling attribute columns

If we only want to plot certain columns of the attribute table we can use argument zcol. Each column will be rendered as a separate layer. These layers will be colored according to the selected attributes.

mapview(breweries, zcol = c("brewery", "village", "founded"))

Including legends

We can also include legends for the layers. Be careful, though, as it is currently not possible to link legends to layers so we end up with too many legends to fit the viewer window if we want to visualize many layers. This is also the reason why legends are not shown by default.

mapview(breweries, zcol = "founded", legend = TRUE)

Raster data

mapview includes 3 raster type data sets:

  • elevation - a digital elevation model of Franconia
  • poppendorf - a RasterBrick including 5 bands of a landsat scene located in Franconia
  • kiliNDVI - a raw multiband raster data set of 23 16-day Aqua-MODIS NDVI layers of Mt. Kilimanajro in Tanzania for the year 2013. See Detsch et al. 2016 for details on how this data set was created

Here’s an example for each raster type (including a sp::SpatialPixelsDataFrame):

RasterLayer

mapview(elevation)

RasterStack/Brick

This will produce one map view layer for each layer in the stack/brick. Use the layers control to switch between the layers. By default all layers are shown (see chapter advanced for an example on how to hide all but one layer).

mapview(poppendorf)

SpatialGridDataFrame

Depending on the number of attribute columns, this is either rendered as a RasterLayer or RasterBrick.

library(mapview)
library(raster)
library(sp)

# SpatialPixelsDataFrame
data(meuse.grid)
coordinates(meuse.grid) <- ~x+y
proj4string(meuse.grid) <- CRS("+init=epsg:28992")
gridded(meuse.grid) <- TRUE

mapView(meuse.grid)

Similar to the vector data functionality, if we want to render a certain column of the attribute table, we can use the zcol argument

library(mapview)
library(raster)
library(sp)

# SpatialPixelsDataFrame
data(meuse.grid)
coordinates(meuse.grid) <- ~x+y
proj4string(meuse.grid) <- CRS("+init=epsg:28992")
gridded(meuse.grid) <- TRUE

mapView(meuse.grid, zcol = "soil")

Identical to vector data plots use legend = TRUE to add legend(s) to raster visualizations.

mapview(elevation, legend = TRUE)